Diagnosis of Fibrosis Using Blood Markers and Logistic Regression in Southeast Asian Patients With Non-alcoholic Fatty Liver Disease - Sang, Chao; Yan, Hongmei; Chan, Wah Kheong; Zhu, Xiaopeng; Sun, Tao; Chang, Xinxia; Xia, Mingfeng; Sun, Xiaoyang; Hu, Xiqi; Gao, Xin; Jia, Wei; Bian, Hua; et al. (Frontiers in Medicine, 2021)
Non-alcoholic fatty liver disease (NAFLD) is one of the important causes of fibrosis. Liver biopsy remains to be the gold standard for fibrosis confirmation in NAFLD patients. Effective and noninvasive diagnosis of advanced fibrosis is essential to disease surveillance and treatment decision. Here, we constructed and validated a simple logistic regression model to screen out advanced fibrosis in NAFLD patients from China, Malaysia, and India (n1=540, n2=147, and n3=97) who were confirmed by liver-biopsy. Nine parameters including age, body mass index, fasting blood glucose, presence of diabetes or impaired fasting glycemia, alanine aminotransferase, γ-glutamyl transferase, triglyceride, and aminotransferase/platelet count ratio, were selected by stepwise logistic regression, receiver operating characteristic curve, and hypothesis testing and were used for model construction. The area under ROC (auROC) of the model was 0.82 for differentiating early and advanced fibrosis (sensitivity=0.69, when specificity=0.80) in the discovery set. Its diagnosis ability remained good in two independent validation sets (auROC=0.89 and 0.71) and was consistently superior to existing panels like FIB-4 and NAFLD Fibrosis Score. A web-based tool, LiveFbr, was developed for fast access to our model. The new model may serve as an attractive tool for advanced fibrosis assessments in NAFLD patients.